Multisystem Inflammatory Syndrome Following SARS-CoV-2 Vaccination in Two Children
Bibliographic record
Abstract
This report presents 2 pediatric cases of multisystem inflammatory syndrome in children and adults (MIS-C/A) post severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination (MIS-V). Both children presented with MIS-V within 6 weeks of receiving their first and only dose of Pfizer-BioNTech's SARS-CoV-2 vaccine. The first patient had symptoms of MIS-C/A with peri-myocarditis and shock, and the second 1 had classic Kawasaki disease features. Both responded well to intravenous immunoglobulins and/or systemic corticosteroids. Both children were positive only for SARS-2-CoV antispike (S) (and not for antinucleocapsid [NC]) antibodies consistent with a postvaccine, and not a postinfection, event. Surveillance for rare adverse events following immunization should continue, especially now that SARS-CoV-2 vaccination is approved in the 5 to 11 year age group that has had the highest risk of developing MIS-C post SARS-CoV-2 infection. Our patients did not receive any further SARS-CoV-2 vaccines. Our report highlights the importance of measuring differentiating antibodies (anti-S and anti-NC) that can be used within a specific timeframe to help determine if a patient has MIS-V post vaccine (only anti-S present), or MIS-C/A post SARS-CoV-2 infection (both anti-S and anti-NC present).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".